One of the primary goals of this 1NIA is to identify behavioral neuroadaptations that occur in the brain reward circuits associated with the extended amygdala and its connections that result in excessive ethanol consumption. In these proposed experiments, a model of excessive ethanol self-administration will be applied to several mouse lines/strains that have unique genotypes hypothesized to be related to the link between ethanol self-administration and extended amygdala function (anxiety-like behaviors and reward function following dependence). Mice will be trained to self-administer ethanol in an operant paradigm, made dependent using an ethanol-containing liquid diet and then exposed to operant ethanol self-administration during repeated bouts of withdrawal. It is predicted that the development of an association between ethanol self-administration and the attenuation of affective withdrawal symptoms will result in excessive ethanol consumption. It is hypothesized that withdrawal is associated with increased I anxiety-like behavior and increased responsiveness to stressor exposure and that both contribute to increasing ethanol consumption in dependent animals. In addition, neurochemistry within the extended amygdala (central and medial nuclei of the amygdala and the BNST) will be manipulated in order to more directly characterize the role of this circuitry in excessive ethanol consumption. It is hypothesized that the corticotropin releasing factor (CRF) and opioid systems in the amygdala are involved in excessive ethanol self-administration and anxiety-like behavior in dependent mice. The implication from these findings is that the control of anxiety in alcoholics is extremely important in reducing relapse. The investigation of neuronal systems that mediate anxiety with regard to their contribution to alcohol self- administration may ultimately lead to more effective treatment approaches to the chronically relapsing disease of alcoholism. This INIA makes use of several Genetic Animal Models Core Components, relates well to other INIA UOls, and also will provide input to the Gene Expression, Imaging and the Bioinformatics Cores.